Join our team as a Data Engineer and contribute to designing, developing, and maintaining robust data solutions. This role is pivotal in managing data generation, collection, and processing activities, ensuring efficient data pipelines and high data quality. You will implement essential ETL processes for seamless data migration and deployment across systems, building a reliable and scalable data infrastructure to support organizational goals.

We are looking for a proactive individual who can independently become a subject matter expert and actively participate in team discussions. Your contributions will be vital in solving work-related challenges and collaborating with cross-functional teams to deliver impactful data solutions. Continuous monitoring and optimization of data pipelines are key to enhancing performance and reliability. You will also be responsible for documenting processes and workflows to foster knowledge sharing and provide guidance to junior team members, promoting their professional development.

Design, develop, and maintain data solutions for data generation, collection, and processing. Create efficient data pipelines and ensure high data quality. Implement ETL (extract, transform, and load) processes for data migration and deployment. Actively participate in team discussions and contribute to problem-solving. Collaborate with cross-functional teams to understand data requirements and deliver effective solutions. Continuously monitor and optimize data pipelines for improved performance and reliability. Document processes and workflows for clear communication and knowledge sharing. Assist and mentor junior team members, supporting their professional growth.

Proven proficiency in PySpark is essential for this role. Experience with Amazon Web Services (AWS), DevOps, and GitLab CI/CD is highly desirable. Possess a strong understanding of data pipeline architecture and best practices in data processing. Demonstrate experience in building scalable and fault-tolerant ETL workflows. Familiarity with distributed computing frameworks and big data technologies is expected. Ability to effectively troubleshoot and resolve complex data processing issues. Minimum of 3 years of experience in Data Engineering, with a focus on PySpark. A full-time education spanning 15 years is required.